On 21 March 2020, Inria launched a dedicated mission to coordinate the mobilization of the institute in the fight against Covid-19 and prioritize the actions.
In its first phase the Covid-19 mission led by Hugues Berry and Philippe Gesnouin, accompanied the launch of projects in response to identified requests from first line players involved in the health crisis (clinicians, hospital staff, epidemiologists, public authorities and patient associations). The mission focused on providing operational solutions within a short timeframe. Proposals were examined on the fly, more than thirty projects have been started between March and early May.
These projects demonstrate the unprecedented commitment of all Inria members from researchers to engineers and members of the support services.
The contagiousness of Covid-19 infection increased the number of patients with acute respiratory distress syndrome and the need for resuscitation beds. In order to better anticipate the need for resuscitation bed openings, it appeared crucial to monitor the evolution of the number of resuscitation beds available in hospitals.
The ParlonsMaths project was born out of an initiative by Animath volunteers to offer original presentations, around mathematics, during the confinement period, to students from 6th to 12th grade, particularly during the spring break which lasts throughout the month of April, 2020.
A web platform for maintaining the link with families for patients in intensive care, often unconscious, PréLifa has been operational since the beginning of the crisis at Lariboisière Hospital. Created in partnership with the Hippocad company, PréLifa’s use is now being extended to all AP-HP hospitals.
The Covid@Keydiag project was born out of the circumstances of the epidemic but takes its roots several years earlier from the meeting between Dr Jean-Noël Ravey, head of the osteo-articular imaging department at Grenoble University Hospital, and Lionel Reveret, expert at Inria in anatomical motion modeling.
What if the combined analysis of our health data allowed health workers to predict and refine the severity of the virus attack? A scientific feat made possible by artificial intelligence thanks to the collaboration between the Gustave Roussy Institute, the Kremlin-Bicêtre Hospital - APHP, the Owkin startup and Inria.
In the current pandemic environment, the AP-HP needs to continuously monitor the flow of Covid-19 patients. The partnership with Inria has led to the development of a tailor-made tool to visualize and monitor data from more than 100,000 patients.
The Linkage.fr platform allows the analysis and synthesis of scientific literature on a given subject, "Covid-19" for example. Linkage allows medical doctors and researchers to follow publications on a given subject while analyzing the research topics addressed.
Face Au Virus est une initiative scientifique ouverte ayant pour objectifs de contribuer à l’information générale sur l’épidémie ainsi qu’à la définition et au suivi des politiques publiques de gestion de crise.
With the development of the Covid-19 pandemic and the droplet mode of contamination, the need for individual protection was quickly expressed through the media. It became essential to provide visors for eye protection, which provided a gateway for the virus to enter.
What if virtual reality could help to rehabilitate Covid-19 patients ? An innovative concept implemented in record time thanks to a close collaboration between the Hybrid project team and the teams from the intensive care of Rennes University Hospital.
Widespread containment of populations during the Covid-19 outbreak was often difficult for the expatriates. Benjamin Guedj created a platform for mutual aid, using data processing and automation skills.
Une équipe pluridisciplinaire de médecins, de chercheurs en robotique et d'ergonomes a collaboré pour fournir des exosquelettes au personnel médical travaillant avec les patients Covid-19 afin de soulager leurs contraintes physiques.
Face au manque d’équipements d’assistance respiratoire et au nombre important de patients atteints par le COVID 19, le projet MaskDecath visait à imprimer en 3D un adaptateur pour transformer un masque de plongée Décathlon en un appareil CPAP à bas prix.
The GestEpid project aims to quantify the impact of sanitary containment and decontainment measures using dynamic model methods. The Sistm project-team is currently working on the prediction of a possible second epidemic wave.
The HealthyMobility project aims to optimize the socio-economic constraints of a target containment, while respecting health constraints. The Necs-Post team works in the field of modelling, estimation and control of large-scale systems.
The objective of the Rantanplan project is to develop an augmented reality application that allows for an interactive visualization of how these new concepts are translated into space, and to make these principles intelligible and concrete for everyone.
Covidom is a home monitoring solution for patients who are Covid-19 carriers or suspected Covid-19 suspects, co-built with AP-HP and Nouveal e-santé. The project leaders proposed complementary approaches to analyse the data from this solution.
RadioCovid was born out of the circumstances of the epidemic. The project proposes to use image analysis, Machine Learning and Deep Learning tools to assist in the diagnosis and, above all, the prognosis of disease progression in the management of patients on the basis of lung imaging (CT scans) and associated biological and clinical data.
The 3DMedifix project was initiated to meet the needs of healthcare personnel, in particular to produce lightweight transparent visors for emergency use. The visors complement existing protection and can be worn over FFP masks to further protect the face from possible projections.
The Covid-19 pandemic has triggered a large number of scientific studies that resorted to numerical simulations of droplet dispersion in order to design social distancing measures. The project Spreading_Factors aims at setting up a methodology to help quantify the relative importance between the input physical parameters and their impact on droplet dispersion as well as to quantify uncertainties on the output results.